arXiv subjects

Pratik Kumar

Publications and source records attributed to Pratik Kumar.

10 recordsLinked to original sources

arXiv2026

50-250 MHz Pulsar Census with an SKA-Low prototype station: Spectra and Polarization

Low-frequency pulsar observations are crucial for understanding pulsar emission spectra and population physics, as well as for probing the interstellar medium (ISM) and Earth's ionosphere. We report the largest low-frequency pulsar census conducted in the southern hemisphere, covering 50-250 MHz, using the EDA2, an SKA-Low prototype station. In this survey, we detected 120 pulsars, including 23 first-time detections below 150 MHz and 5 below 100 MHz. For each source, we provide integrated pulse profiles and flux-density measurements across five sub-bands spanning 50-250 MHz. We also obtained improved dispersion measure (DM) values for 110 pulsars, with a median absolute DM correction of about 0.1 pc cm^-3. We measured significant Faraday rotation for 40 pulsars with improved rotation measure (RM) values for 4 pulsars, as well as phase-resolved RM variation in J1453-6413. Full-polarimetric pulse profiles are provided for all these pulsars, with multi-frequency polarimetric data for 20 of them. These results will enhance future SKA-Low science: refining pulsar population models, informing survey strategies, and advancing characterization of both the ISM and the ionosphere through low-frequency pulsar monitoring.

astro-ph.HE↗

arXiv2025

Pulsar B1237+25 Aberration/Retardation Analysis from Decimeter to Decameter Wavelength: Challenge to "Radius-to-Frequency Mapping"

PSR B1237+25 is perhaps the canonical example of a pulsar with a core/double cone profile. Moreover, it is bright with little spectral turnover, and its profile perhaps uniquely remains undistorted by scattering far into the decametric band. Here we assemble more than a dozen of the highest quality profiles (30 MHz to 5 GHz) from half a dozen observatories, where possible polarimetric. The pulsar's 2.6$^{\circ}$ core component marks the magnetic axis longitude, and we confirm that this point coincides both with the linear polarization angle inflection point and the zero-crossing of its antisymmetric circular signature -- thus providing the possibility to estimate emission heights over a very broad band using aberration/retardation (A/R). We then carefully fit the profile components with Gaussians to identify and study the subtle asymmetries produced by A/R. We find a consistent A/R in the pulsar's profiles of some 0.5$^{\circ}$ longitude or 2 ms -- corresponding to a putative conal emission height of 200-400 km -- with a formal error of about 100 km. Our analysis finds no evidence whatsoever for an emission height increase with wavelength, the so-called ``radius-to-frequency mapping''. Nor do we find any significant difference in A/R effect between the outer and inner cones.

astro-ph.HE↗

arXiv2025

A Multifrequency Census of 100 Pulsars below 100 MHz with LWA: A Systematic Study of Flux Density, Spectra, Timing, Dispersion, Polarization, and Its Variation from a Decade of Observations

We present a census of 100 pulsars, the largest below 100 MHz, including 94 normal pulsars and six millisecond pulsars, with the Long Wavelength Array (LWA). Pulse profiles are detected across a range of frequencies from 26 to 88 MHz, including new narrow-band profiles facilitating profile evolution studies and breaks in pulsar spectra at low frequencies. We report mean flux density, spectral index, curvature, and low-frequency turnover frequency measurements for 97 pulsars, including new measurements for 61 sources. Multi-frequency profile widths are presented for all pulsars, including component spacing for 27 pulsars with two components. Polarized emission is detected from 27 of the sources (the largest sample at these frequencies) in multiple frequency bands, with one new detection. We also provide new timing solutions for five recently-discovered pulsars. Low-frequency observations with the LWA are especially sensitive to propagation effects arising in the interstellar medium. We have made the most sensitive measurements of pulsar dispersion measures (DMs) and rotation measures (RMs), with median uncertainties of 2.9x10^-4 pc cm^-3 and 0.01 rad m^-2, respectively, and can track their variations over almost a decade, along with other frequency-dependent effects. This allows stringent limits on average magnetic fields, with no variations detected above ~20 nG. Finally, the census yields some interesting phenomena in individual sources, including the detection of frequency and time-dependent DM variations in B2217+47, and the detection of highly circularly polarized emission from J0051+0423.

astro-ph.HE↗

arXiv2023

Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach

Lattice reduction is a combinatorial optimization problem aimed at finding the most orthogonal basis in a given lattice. The Lenstra-Lenstra-Lov\'asz (LLL) algorithm is the best algorithm in the literature for solving this problem. In light of recent research on algorithm discovery, in this work, we would like to answer this question: is it possible to parametrize the algorithm space for lattice reduction problem with neural networks and find an algorithm without supervised data? Our strategy is to use equivariant and invariant parametrizations and train in a self-supervised way. We design a deep neural model outputting factorized unimodular matrices and train it in a self-supervised manner by penalizing non-orthogonal lattice bases. We incorporate the symmetries of lattice reduction into the model by making it invariant to isometries and scaling of the ambient space and equivariant with respect to the hyperocrahedral group permuting and flipping the lattice basis elements. We show that this approach yields an algorithm with comparable complexity and performance to the LLL algorithm on a set of benchmarks. Additionally, motivated by certain applications for wireless communication, we extend our method to a convolutional architecture which performs joint reduction of spatially-correlated lattices arranged in a grid, thereby amortizing its cost over multiple lattices.

cs.LG↗

arXiv2022

High-Frequency Tunable Resistorless Memcapacitor Emulator and Application

In this paper, a new design has been proposed for the realization of high-frequency memcapacitor emulators built with three OTAs. This paper also proposes the application of memcapacitor as an amplitude modulator. Furthermore, applications of memcapacitor as a filter, Oscillator point attractor, and periodic doubler are also shown. The proposed circuits can be configured in both incremental and decremental topology. The proposed circuits and their application claim that the circuit is much simpler in design and can be utilized in both topologies. The performance of all the proposed circuits has been verified on Cadence Virtuoso Spectre using standard CMOS 180nm. Furthermore, post-layout simulations and their comparison have been carried out.

eess.SP↗

arXiv2022

High-Frequency Tunable Grounded & Floating Incremental-Decremental Meminductor Emulator and Application

This paper proposes a new design for realizing grounded and floating meminductor emulators built with two operational transconductance amplifiers (OTAs) and two second-generation current conveyors. The proposed grounded and floating emulators claim that the circuits are much simpler in design and can be utilized in incremental and decremental topologies. The proposed circuits' performance has been verified with Cadence Virtuoso Spectre using standard CMOS 180nm technology. Furthermore, the layout of the proposed circuits has been designed, and post-layout simulations have been performed. The non-ideal and Monte Carlo analyses have been carried out in detail. This paper also proposes the application of a meminductor as an Amplitude Modulator (AM). Moreover, the experimental results are presented to verify the theoretical and simulation analyses of proposed meminductor emulator circuits.

eess.SP↗

arXiv2022

Process, Bias and Temperature Scalable CMOS Analog Computing Circuits for Machine Learning

Analog computing is attractive compared to digital computing due to its potential for achieving higher computational density and higher energy efficiency. However, unlike digital circuits, conventional analog computing circuits cannot be easily mapped across different process nodes due to differences in transistor biasing regimes, temperature variations and limited dynamic range. In this work, we generalize the previously reported margin-propagation-based analog computing framework for designing novel \textit{shape-based analog computing} (S-AC) circuits that can be easily cross-mapped across different process nodes. Similar to digital designs S-AC designs can also be scaled for precision, speed, and power. As a proof-of-concept, we show several examples of S-AC circuits implementing mathematical functions that are commonly used in machine learning (ML) architectures. Using circuit simulations we demonstrate that the circuit input/output characteristics remain robust when mapped from a planar CMOS 180nm process to a FinFET 7nm process. Also, using benchmark datasets we demonstrate that the classification accuracy of a S-AC based neural network remains robust when mapped across the two processes and to changes in temperature.

cs.AR↗

arXiv2022

Bias-Scalable Near-Memory CMOS Analog Processor for Machine Learning

Bias-scalable analog computing is attractive for implementing machine learning (ML) processors with distinct power-performance specifications. For instance, ML implementations for server workloads are focused on higher computational throughput for faster training, whereas ML implementations for edge devices are focused on energy-efficient inference. In this paper, we demonstrate the implementation of bias-scalable approximate analog computing circuits using the generalization of the margin-propagation principle called shape-based analog computing (S-AC). The resulting S-AC core integrates several near-memory compute elements, which include: (a) non-linear activation functions; (b) inner-product compute circuits; and (c) a mixed-signal compressive memory, all of which can be scaled for performance or power while preserving its functionality. Using measured results from prototypes fabricated in a 180nm CMOS process, we demonstrate that the performance of computing modules remains robust to transistor biasing and variations in temperature. In this paper, we also demonstrate the effect of bias-scalability and computational accuracy on a simple ML regression task.

cs.ET↗

arXiv2021

Investigating Bias In Automatic Toxic Comment Detection: An Empirical Study

With surge in online platforms, there has been an upsurge in the user engagement on these platforms via comments and reactions. A large portion of such textual comments are abusive, rude and offensive to the audience. With machine learning systems in-place to check such comments coming onto platform, biases present in the training data gets passed onto the classifier leading to discrimination against a set of classes, religion and gender. In this work, we evaluate different classifiers and feature to estimate the bias in these classifiers along with their performance on downstream task of toxicity classification. Results show that improvement in performance of automatic toxic comment detection models is positively correlated to mitigating biases in these models. In our work, LSTM with attention mechanism proved to be a better modelling strategy than a CNN model. Further analysis shows that fasttext embeddings is marginally preferable than glove embeddings on training models for toxicity comment detection. Deeper analysis reveals the findings that such automatic models are particularly biased to specific identity groups even though the model has a high AUC score. Finally, in effort to mitigate bias in toxicity detection models, a multi-task setup trained with auxiliary task of toxicity sub-types proved to be useful leading to upto 0.26% (6% relative) gain in AUC scores.

cs.CL↗

arXiv2016

Everyday Radio Telescope

We have developed an affordable, portable college level radio telescope for amateur radio astronomy which can be used to provide hands-on experience with the fundamentals of a radio telescope and an insight into the realm of radio astronomy. With our set-up one can measure brightness temperature and flux of the Sun at 11.2 GHz and calculate the beam width of the antenna. The set-up uses commercially available satellite television receiving system and parabolic dish antenna. We report the detection of point sources like Saturn and extended sources like the galactic arm of the Milky way. We have also developed python pipeline, which are available for free download, for data acquisition and visualization.

physics.ed-ph↗